A novel evidence-based algorithm to predict thromboembolism in patients with COVID-19: preliminary data from a single-centre cohort
Academic Article
Publication Date:
2022
abstract:
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-related disease (COVID-19) is an infectious disease characterised by systemic inflammation, which might enhance baseline thrombotic risk, especially in hospitalised patients. Little is, however, known about predictors of thrombotic complications in patients with COVID-19.
Iris type:
1.1 Articolo in rivista
List of contributors:
Ramirez, Giuseppe A; Calvisi, Stefania L; De Lorenzo, Rebecca; Da Prat, Valentina; Borio, Giorgia; Gallina, Gabriele; Farolfi, Federica; Cavallo, Ludovica; Pascali, Maria; Castellani, Jacopo; Baccellieri, Domenico; Guzzo, Francesca; Baiardo Redaelli, Martina; Azzolini, Maria Luisa; Alba, Ada C; Zangrillo, Alberto; Bozzolo, Enrica P; Scotti, Raffaella; Di Lucca, Giuseppe; Piemonti, Lorenzo; Rovere Querini, Patrizia; D'Angelo, Armando; Tresoldi, Moreno (COVID-BioB group); Landoni, G
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